Person name matching is a very important technology in the risk control field. For example, a risk control system records person names of determined unauthorized users in a blacklist. Then, when performing risk control operation, for each user that currently performs a service, a person name of each user is matched with each person name in the blacklist through scanning. If the matching succeeds, the user can be considered as an unauthorized user, and the service of the user is rejected, to prevent certain risks.
Person name matching can be classified into accurate person name matching and person name fuzzy matching. In comparison, person name fuzzy matching is more difficult in terms of technologies because it is difficult to control a proper fuzzy degree.
In the existing technology, a string matching algorithm is usually used to perform person name fuzzy matching, and a string matching degree threshold determines a fuzzy degree. However, the string matching degree threshold is all set according to experience. To reduce omission, the string matching degree threshold is usually set to a relatively low value. Consequently, the matching accuracy is relatively low, and a false alarm rate of the risk control system is relatively high.